Comparar métodos
Examine os métodos selecionados lado a lado; as linhas que diferem ficam destacadas.
| Modelo de Efeitos Fixos em Painel× | Modelo de Efeitos Aleatórios em Painel× | |
|---|---|---|
| Área | Econometria | Econometria |
| Família | Regression model | Regression model |
| Ano de origem≠ | 1978 | 1966 |
| Autor original≠ | Mundlak (1978); classical treatment in Wooldridge (2010) and Baltagi (2021) | Balestra & Nerlove |
| Tipo≠ | Panel regression estimator | Panel data estimator |
| Fonte seminal≠ | Wooldridge, J. M. (2010). Econometric Analysis of Cross Section and Panel Data (2nd ed.). MIT Press. ISBN: 978-0262232586 | Balestra, P., & Nerlove, M. (1966). Pooling cross section and time series data in the estimation of a dynamic model: The demand for natural gas. Econometrica, 34(3), 585–612. DOI ↗ |
| Outros nomes | within estimator, FE model, within-group estimator, LSDV model | random effects estimator, RE model, GLS random effects, error components model |
| Relacionados | 5 | 5 |
| Resumo≠ | The panel fixed effects (FE) model controls for all time-invariant, unit-specific unobserved heterogeneity by absorbing it into individual intercepts. By sweeping out unit means through the within transformation, FE yields unbiased estimates of the effect of time-varying regressors even when omitted unit-level confounders are correlated with those regressors. | The panel random effects (RE) model treats individual-specific effects as random draws from a population distribution rather than fixed constants, enabling efficient estimation by generalised least squares and allowing inference about time-invariant regressors that are swept away in fixed effects estimation. |
| ScholarGateConjunto de dados ↗ |
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